Blog archive, page 11

Last week Domino celebrated data science innovators driving breakthroughs in health and life sciences. This week we announce a new slate of innovators in the Financial Services and Insurance edition of the Data Science Innovator’s Playbook, available now as a free download. As before, each of its top data science innovation leaders in the financial services and insurance industries share insights on their work, careers, and the data science profession. The playbook includes seven profiles, the first being of Dr. Tiffany Perkins-Munn.

Innovation is the magic word for improvement: a new idea, a different process, a methodology change that can mean all the difference in business value. If you are a data science leader or practitioner either working in or seeking information about healthcare and pharmaceutical industries, Domino created an eBook of new ideas by five peer innovators in this domain. Tailored just for you!

In a never-ending quest to accelerate innovation, healthcare and pharmaceutical companies around the world have been working to modernize their statistical computing environments, streamline clinical trials, and handle the required analytics and reporting.

I am fortunate to work with some of the most sophisticated global companies on their AI/ML initiatives. These companies include many household names on the Fortune 500 and come from industries as diverse as insurance, pharmaceuticals, and manufacturing. Each has dozens to literally thousands of data scientists on its payroll. While they have significant investments in AI and ML, they exhibit a surprisingly wide array of maturity when it comes to MLOps.

When it comes to the pharmaceutical industries, machine learning, AI, and statistical computing environments (SCEs) often receive the lion’s share of media attention and seize the popular imagination in coverage that focuses mostly on technology aimed at finding interesting chemical candidates for the next breakthrough cure. But there’s a second, far more rarely covered role of data science in the quest for new cures, one that Andy Nicholls, GSK’s senior director and head of statistical data sciences, discusses inThe Data Science Innovator’s Playbook.

Deep learning is a type of machine learning and artificial intelligence (AI) that imitates how humans learn by example. While that sounds complex, the basic idea behind deep learning is simple. Deep learning models are taught to classify data from images (such as “cat vs. dog”), sound (“meow vs. bark”), or text (“tabby vs. schnauzer”). These models build a hierarchy where each layer is based on knowledge gained from the preceding layer, and iterations continue until its accuracy goal is reached. Deep learning models often achieve accuracy that rivals what humans can determine, in a fraction of the time.